Research on air pollution by PM10 and NO2 pollutants in Slovakia from 2016 to 2022 years

The Chinese government has implemented a number of environmental policies to promote the continuous improvement of air quality while considering economic development. Scientific assessment of the impact of environmental policies on the relationship between air pollution and economic growth can provide a scientific basis for promoting the coordinated development of these two factors. This paper uses the Tapio decoupling theory to analyze the relationship between regional economic growth and air pollution in key regions of air pollution control in China—namely, the Beijing–Tianjin–Hebei region and surrounding areas (BTHS), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD)—based on data of GDP and the concentrations of SO2, PM10, and NO2 for 31 provinces in China from 2000 to 2019. The results show that the SO2, PM10, and NO2 pollution in the key regions show strong and weak decoupling. The findings additionally indicate that government policies have played a significant role in improving the decoupling between air pollution and economic development. The decoupling between economic growth and SO2 and PM10 pollution in the BTHS, YRD, and PRD is better than that in other regions, while the decoupling between economic growth and NO2 pollution has not improved significantly in these regions. To improve the relationship between economic growth and air pollution, we suggest that the governments of China and other developing countries should further optimize and adjust the structure of industry, energy, and transportation; apply more stringent targets and measures in areas of serious air pollution; and strengthen mobile vehicle pollution control.

Objectives:Based on the correlation between air pollution and COVID-19 incidence/mortality already existing in the literature, we aimed to develop a study to investigate the link between the average level of PM10 (particulate matter 10 - particulate matter 10 microns in diameter) and NO2 (nitrogen dioxide) concentration over five years and the cumulative incidence of COVID-19 cases per 1000 people in Romania. Methods: To assess PM10 and NO2 exposure, we determined the average value of annual PM10 and NO2 concentration for each city over five years (2015-2019). For this purpose, the average of annual PM10 and NO2 concentrations collected from monitoring stations in selected cities was calculated. Then, the annual values over five years were averaged to finally obtain the average PM10 and NO2 concentration for each city. Data on the cumulative number of confirmed cases of COVID-19 up to the 28th of September 2020 were provided by the National Centre for Surveillance and Control of Communicable Diseases (CNSCBT) of the National Institute of Public Health (INSP). The study used the cumulative incidence/hour per 1000 population on 28.09.2020. Results:According to Law no. 104/2011, the annual permissible limit value of PM10 concentration of 40 μg/m³ was not exceeded in any of the 43 cities in our study. The average for all cities was 24.0±4.8 ìg/m³, with a minimum value of average PM10 concentration of 13.9 μg/m3 measured in Alba Iulia and a maximum value of 39.1 μg/m³ in Iasi. The regression model shows that, in Bucharest, 77.9% of the variation in case incidence is explained by the variation in PM10 concentration. In order to find the number of new cases that would correspond to a cumulative incidence of 0.166, taking as an example one of the districts with a population of 259,084, the above regression model shows that an increase in the average PM10 concentration by one unit is associated with 43 new cases. Conclusion:The study demonstrates that an exposure of the population to particulate matter in atmospheric air, at low values, below the permissible limit values but for a long time (the follow-up period in our study was five years, between 2015 and 2019), can have effects on the health status of the population, which becomes much more vulnerable to external agents, in our case pathogenic microorganisms (viruses).

Objective: To construct the air quality health index (AQHI) by inclusion of air pollutants PM(2.5) and O(3) in Guangzhou, Shanghai, Xi' an, Beijing, Shenyang, and explore scientificity and feasibility of its application in China. Methods: The daily average concentrations of PM(2.5) and O(3) in air, and daily average mortality from 2013 to 2015 in the 5 cities in China, the exposure-response coefficients of PM(2.5) and O(3) and total mortality from Meta studies in China were used to construct local AQHI. The health risk levels of air pollution in the 5 cities were calculated and compared with the characteristics of single pollutant concentrationof PM(2.5) or O(3). Results: In the 5 cities, the average concentration of PM(2.5) was highest in Beijing (82 μg/m(3)) and lowest in Guangzhou (46 μg/m(3)). And the average concentration of O(3) was highest in Shanghai (72 μg/m(3)) and lowest in Xi' an (45 μg/m(3)). In all the cities, the average concentration of PM(2.5) was highest in winter and lowest in summer. In summer, the average concentration of O(3) was lowest. But the health risk level of AQHI showed that the 5 cities had higher frequency of low or medium risk averagely. And Beijing had the highest frequency of high risk in summer (5.69%). Xi' an had the highest frequency of extremely high risk in winter (1.63%). Conclusions: In this study, AQHI could be constructed by using air PM(2.5) and O(3) concentration data which can be obtained in many areas in China. The application of this index is scientific and feasible in China.

Air quality indicators, i.e., PM10, NO2, O3, benzo[a]pyrene, and several organic tracer compounds were evaluated in an urban traffic station, a sub-urban background station, and a rural background station of the air quality network in Catalonia (Spain) from summer to winter 2019. The main sources that contribute to the organic aerosol and PM toxicity were determined. Traffic-related air pollution dominated the air quality in the urban traffic station, while biomass burning in winter and secondary organic aerosol (SOA) in summer impact the air quality in the sub-urban and rural background stations. Health risk assessment for chronic exposure over the past decade, using WHO air quality standards, showed that NO2, PM10 and benzo[a]pyrene from traffic emissions pose an unacceptable risk to the human population in the urban traffic station. PM10 and benzo[a]pyrene from biomass burning were unacceptably high in the sub-urban and rural background stations. Toxicity tests of the PM extracts with epithelial lung cells showed higher toxicity in wintertime samples in the sub-urban and rural stations, compared to the urban traffic station. These results require different mitigation strategies for urban and rural sites in order to improve the air quality. In urban areas, traffic emissions are still dominating the air quality, despite improvements in the last years, and may directly be responsible for part of the SOA and O3 levels in sub-urban and rural areas. In these later areas, air pollution from local biomass burning emissions are dominating the air quality, essentially in the colder period of the year.

Objective To investigate the relationship between air pollutants and hospitalization rate of children with respiratory disease (asthmatic attack, asthmatoid bronchitis, neumonia) in Shijiazhuang city. Methods The data of air quality monitoring in Shijiazhuang in Hebei Province from January 2016 to December 2016 were recorded, and hospitalization rate of children respiratory disease (asthmatic attack, asthmatoid bronchitis, pneumonia) in Hebei Children′s Hospital were enrolled, and the analysis of the linear regression was done for the correlation of air pollutants and hospitalization rate of children respiratory disease. Results The analysis result showed that the asthmatoid bronchitis hospitalization rate was positively correlated with the average concentration of SO2 and NO2, the correlation coefficient was 0.598 and 0.626 (P<0.05). The results showed that the average concentration of PM10, CO, PM2.5 and O3 did not have linear correlation with asthmatoid bronchitis hospitalization rate.The pneumonia hospitalization rate was positively correlated with the average concentration of SO2, NO2, PM10, CO and PM2.5, and the correlation coefficient was 0.867, 0.811, 0.825, 0.931 and 0.860, respectively (all P<0.05), but was independent with the average concentration of O3.It showed that if the index of concentration of contaminations increase of 10, hospitalization rate of asthmatoid bronchitis increased 0.1% and increased 2.4% of pneumonia. Conclusions The increase of PM10, PM2.5, NO2, SO2 and CO air pollutants could make a corresponding increase in the hospitalization rate of children with respiratory diseases. Key words: Air pollutants; PM2.5; Children; Disease of repiratory system

According to World Health Organization (WHO) and Global Burden of Disease, ambient air pollution is estimated to be responsible for 3.7 million premature deaths in 2012 [1] . Therefore, it is urgent to estimate the impact of air pollution on public health and economic damage. The objectives of this research are: study the distribution of PM10 concentration over Ho Chi Minh city (HCMC) and relationship to public health and for proposing solutions of disease s prevention in HCM, Vietnam. EMIssion SENSitivity model was applied to conduct air emission inventory for transportation sector. Then, Finite Volume Model and Transport and Photochemistry Mesoscale Model were used to simulate the meteorology and the spatial distribution of PM10 in HCMC. Together with disease data obtained, the US Environmental Benefits Mapping and Analysis Model was applied for calculating the number of deaths and estimating economic losses due to PM10 pollution. Finally, solutions to reduce PM10 pollution and protect public health are proposed. The results showed that the highest 1-h average concentration of PM10 is 240 μg m−3 in North Eastern of HCMC. The concentration of PM10 for annual average in District 5 ranged from 17 to 49 μg m−3. There are 12 wards of District 5 with PM10 concentration exceeding the WHO guidelines (20 μg m−3 for annual average of PM10 and 50 μg m−3 for 24-h average). The high concentration of PM10 causes 5 deaths yr−1 in District 5 and 204 deaths yr−1 in HCMC, and it causes economic losses of 1.84 billion of USD.

Physical phenomenon of the relation among the ground level O3, NOx and VOC governed by complex nonlinear photochemistry in urban environments is explained in detail using the ambient pollutant concentration data of eleven cities in Sri Lanka. The time-series analysis was conducted using the 24-hour average ambient concentrations of PM10, NO2, CO, O3 and SO2 air pollutants obtained from fixed air pollution monitoring station located in Colombo since 2008. Further analysis was carried out from the mobile air pollution monitoring station for eleven cities. The hourly averaged ambient real time air quality data i.e. VOC, NO2, NO, O3 pollutants and the corresponding meteorological parameters were analyzed and presented in weekly results for the base year 2013, 2014 and 2015. It was identified that there exist two regimes of NOx-VOC-O3 sensitivity among these cities. Colombo, Kurunegala, Jaffna, Matara, Badulla, Pollonnaruwa, and Gampaha are the NOx-sensitive regime. While Rathnapura, Anuradhapura, Kandy and Nuwaraelliya are the VOC-sensitive regime. In the NOx-sensitive regime (with relatively low NOx and high VOC), O3 increases with the increasing NOx and slightly changes in response to the increasing VOC levels. In the NOx-saturated or VOC-sensitive regime, O3 decreases with increasing NOx level and increases with increasing VOC levels. In the immediate vicinity of very large emissions of NO, O3 concentrations are depressed through the process of NOx titration. Mathematical relationships were developed to calculate the steady state ozone concentration (O3ss) that gives the values for both NOx-sensitive regime and the VOC-sensitive regime. Establishment of these relationships are essential for Sri Lanka to develop the appropriate interventions for controlling O3 pollution in each city.

To the Editor: Higher concentrations of fine particles [particulate matter less than 10 or 2.5 μm in aerodynamic diameter (PM10 or PM2.5)] in the air are often associated with higher death rates from all causes or from cardiovascular and respiratory causes, and many authors have concluded that the associations may be causal. 1–3 Others have questioned the idea as being biologically implausible, or because they consider the statistical evidence to be inadequate to demonstrate a causal relationship. 4 From day-to-day variations in concentrations of PM10 and the associated variations in the number of deaths on the following day in 20 U.S. cities, Samet et al1 calculated that increases of 10 μg of PM10 per cubic meter of air resulted in an average increase of 0.51% in deaths from all causes, and an increase of 0.68% in deaths from cardiovascular and respiratory causes. From the consistency of these and other results, they and Ware 2 concluded that increases in concentration of PM10 were the causal factor in the relationship. Effects on all-cause mortality varied from about −1.0% in Atlanta to about +2.0% in Oakland. As the data from all of the cities were treated uniformly, these variations did not result from different methods of analysis. These real differences may have resulted from the people being more susceptible, the environment being more dangerous, or the PM10 itself being more toxic in some cities than in others. The differences did not depend on average concentrations of PM10 or ozone, or on city-specific demographic characteristics. The differences showed that increases in PM10 were not consistently harmful. From the stated consistency of the effects, Samet et al1 concluded that PM10, the particles themselves, were responsible for the associations. PM10 comes from many sources, and so it may have varied in composition from city to city. Between-city concentrations of PM10 and other pollutants were positively correlated. It was concluded that this “correlation structure generally reflects the common sources of the primary combustion-related gases,”1(p 1744) implying that this showed that the PM10 came from similar sources in the 20 cities, and would be likely to have similar composition and effects. However, proportions of PM10, sulfur dioxide (SO2), and carbon monoxide varied widely from city to city. This suggests that the sources of PM10, and its composition and possible toxicity, may have varied quantitatively between cities. The effects of daily variations in the concentrations of ozone were also calculated, and overall these were said to be concentrated near zero. In fact, each increase of 10 ppb in ozone concentration was associated with a small mean reduction of about 0.35% (±0.36; 95% confidence limits = −0.01, 0.71) in deaths. This association varied between winter and summer. From the data in Tables 1 and 2 of Samet et al, 1 we have calculated the correlations between death rates from respiratory and cardiovascular causes and mean concentrations of listed pollutants. The relationships with PM10 and SO2 are graphed in Figures 1 and 2.FIGURE 1: Mean daily death rates from cardiovascular and respiratory causes in 20 U.S. cities plotted against mean PM10 concentrations. Data from Tables 1 and 2 of Samet et al. 1FIGURE 2: Mean daily death rates from cardiovascular and respiratory causes in 15 U.S. cities plotted against mean SO2 concentrations. Data from Tables 1 and 2 of Samet et al. 1Between-city variations in death rates were weakly and nonsignificantly correlated with variations in mean concentrations of PM10 (r = +0.26;Figure 1), as well as carbon monoxide (r = +0.25), nitrogen dioxide (r = +0.27), and ozone (r = −0.09) (data not shown in figures). They were, however, highly correlated with variations in concentrations of SO2 (r = +0.88, P < 0.01;Figure 2). Day-to-day variations in concentrations of SO2 were not associated with corresponding daily variations in deaths. These apparently anomalous and inconsistent results were not discussed by Samet et al. 1 They could perhaps be explained if PM10 varied in toxicity from city to city, and if the higher death rates after high PM10 pollution days were merely hastening by a few days the deaths of those already near death. Samet et al, 1 and other authors whom they cited, have considered this latter explanation but have generally dismissed it. In our opinion, the statistical data do not show that reducing concentrations of PM10 will prolong life. We thank Grant McKenzie, Animal and Food Sciences Division, Lincoln University, for composing the graphs. Pat Palmer David Saville

ObjectiveTo assess the health risks associated with exposure to particulate matter (PM10), sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO) and ozone (O3).DesignThe study is an ecological study that...

Gaseous pollutant emissions from brick kiln industries deteriorate the current state of ambient air quality in Pakistan and worldwide. These gaseous pollutants affect the health of plants and may decrease plant growth and yield. A field experiment that was conducted to monitor the concentration of gaseous pollutants emitted mainly from brick kilns in the ambient air and associated impacts on the growth and physiological attributes of the two wheat (Triticum spp.) cultivars. Plants were grown at three sites, including control (Ayub Agriculture Research Institute, AARI), low pollution (LP) site (Small Estate Industry), and high pollution (HP) site (Sidar Bypass), of Faisalabad, Pakistan. Monitoring of ambient air pollution at experimental sites was carried out using the state-of-art ambient air analyzers. Plants were harvested after 120 days of germination and were analyzed for different growth attributes. Results showed that the hourly average concentration of gaseous air pollutants CO, NO2, SO2, and PM10 at HP site were significantly higher than the LP and control sites. Similarly, gaseous pollutants decreased plant height, straw and grain yield, photosynthesis and increased physical injury, and metal concentrations in the grains. However, wheat response toward gaseous pollutants did not differ between cultivars (Galaxy and 8173) studied. Overall, the results indicated that brick kiln emissions could reduce the performance of wheat grown in the soils around kilns and confirm the adverse impacts of pollutants on the growth, yield, and quality of the wheat.

Introduction: The aim of this study was to investigate the concentrations of PM10, PM2.5, O3, NO2, SO2, and CO in Tehran during March 2014-March 2018, and evaluate the effects of holidays and meteorological parameters on the air pollution levels. Materials and methods: Hourly concentrations of PM10, PM2.5, O3, NO2, SO2, and CO in different air quality monitors of Tehran were acquired. The data from each air quality monitored were validated, and only high-quality monitors were included in this study. Results: The 4-year averages of PM10, PM2.5, O3, NO2, SO2, and CO concen-trations were 88.74 (µg/m3), 31.02 (µg/m3), 34.87 (ppb), 71.01 (ppb), 20.04 (ppb), and 3.78 (ppm), respectively. Higher concentrations of PM10 and O3 were observed during summer. In case of PM2.5 and CO, autumn and winter concentrations were higher than those in springer and summer. Lower concen-trations of PM10 and NO2 in Fridays were observed comparing to other days of week. Ozone had high concentrations in Fridays as the weekend in Iran. Except for O3, all of the pollutants had higher concentrations in the working days, comparing to those in any type of vacation days. Concentrations of all pollutants rather that SO2 and O3 in Nowruz holidays were statistically lower than those in the working days. By controlling for the effects of meteorologi-cal variables, our results showed that the air pollution control policies and ac-tions have been not effective for particulate matter. Conclusion: These results determines the time periods in which the concen-trations of criteria air pollutants are high. This can be very useful for an-nouncing alarms for citizens, and designing the air pollution control plans. In addition, more effective actions should be designed and implemented for reducing ambient levels of particulate matter.

Abstract. The trends and variability of PM10, PM2.5 and PMcoarse concentrations at seven urban and rural background stations in five European countries for the period between 1998 and 2010 were investigated. Collocated or nearby PM measurements and meteorological observations were used in order to construct Generalized Additive Models, which model the effect of each meteorological variable on PM concentrations. In agreement with previous findings, the most important meteorological variables affecting PM concentrations were wind speed, wind direction, boundary layer depth, precipitation, temperature and number of consecutive days with synoptic weather patterns that favor high PM concentrations. Temperature has a negative relationship to PM2.5 concentrations for low temperatures and a positive relationship for high temperatures. The stationary point of this relationship varies between 5 and 15 °C depending on the station. PMcoarse concentrations increase for increasing temperatures almost throughout the temperature range. Wind speed has a monotonic relationship to PM2.5 except for one station, which exhibits a stationary point. Considering PMcoarse, concentrations tend to increase or stabilize for large wind speeds at most stations. It was also observed that at all stations except one, higher PM2.5 concentrations occurred for east wind direction, compared to west wind direction. Meteorologically adjusted PM time series were produced by removing most of the PM variability due to meteorology. It was found that PM10 and PM2.5 concentrations decrease at most stations. The average trends of the raw and meteorologically adjusted data are −0.4 μg m−3 yr−1 for PM10 and PM2.5 size fractions. PMcoarse have much smaller trends and after averaging over all stations, no significant trend was detected at the 95% level of confidence. It is suggested that decreasing PMcoarse in addition to PM2.5 can result in a faster decrease of PM10 in the future. The trends of the 90th quantile of PM10 and PM2.5 concentrations were examined by quantile regression in order to detect long term changes in the occurrence of very large PM concentrations. The meteorologically adjusted trends of the 90th quantile were significantly larger (as an absolute value) on average over all stations (−0.6 μg m−3 yr−1).

Present study is an attempt to estimate the effects of roadside dust pollution on apple trees of Mohal (1146 m), Raison (1359 m) and one control site, Beasar (2181 m), Kullu Valley, Himachal Pradesh. In both Mohal and Raison sites, PM10 and PM2.5 are showing the increasing trend which is affecting the apple farming and production in the area. When the dust particles settle down on the stigma of flower it stops an anther to contact with stigma, which affects the pollination. Thus, the dust particle affects the flower of plant during the time of pollination. Particulate pollutants PM10 (<10 μm) and PM2.5 (<2.5 μm) have been monitored in and around of apple orchards. Average PM10 concentration has found low (20.9 ± 1.7 µg m−3) at control site Beasar, whereas it shows high value (88.1 ± 2.0 µg m−3) at Raison. Mohal has relatively higher PM10 concentration with a mean value of 104.2 ± 1.1 µg m−3. In Mohal and Raison sites, the particulate pollutants have µcrossed the permissible limit (100 µg m−3) as prescribed by National Ambient Air Quality Standards (NAAQS). There is negative correlation with NDVI values and pollutants concentration. It is also made clear from HYSPLIT model and CALIPSO analysis that the sources of pollutants are mainly local in nature. The Air Quality Index (AQI) study reveals that air quality of Mohal falls under good condition. But during spring season, the pollutants cross the permissible limit which affects the pollination process of apple trees.KeywordsParticulate pollutantsPM10PM2.5Kullu valleyApple orchards

Investigating the multiscale associations between urban landscape patterns and PM1 pollution in China using a new combined framework

Stronger susceptibilities to air pollutants of influenza A than B were identified in subtropical Shenzhen, China